Skilful forecasting of monthly streamflow in intermittent rivers is a challenging task in stochastic hydrology. In this study, genetic algorithm (GA) was combined with gene expression programming (GEP) as a new hybrid model ...

A precise forecast of streamflow in intermittent rivers is of major difficulties and challenges in watershed management, particularly in arid and semiarid regions. The present research study introduces an ensemble gene ...

Long-term prediction of rainfalls is one of the most challenging tasks in stochastic hydrology owing to the highly random characteristics of rainfall events. In this paper, a novel approach is adopted to develop a hybrid ...

It is known that construction of large sewers based on consideration of flow with non-deposition without a bed deposit is not economical. Sewer design based on consideration of flow with non-deposition with a bed deposit ...

Using regionally downscaled and adjusted outputs of three global climate models (GCMs), meteorological drought analysis was accomplished across Ankara, the capital city of Turkey. To this end, standardized precipitation ...

This paper presents a new tree-based model, namely Fuzzy Random Forest (FRF), for one month ahead Standardized Precipitation Evapotranspiration Index (SPEI) classification and prediction with a noteworthy application in ...

Rainfall is considered the hardest weather variable to forecast, and its cause-effect relationships often cannot be expressed in simple or complex mathematical forms. This study introduces a novel hybrid model to month ...

The state-of-the-art genetic programming (GP) method is an evolutionary algorithm for automatic generation of computer programs. In recent decades, GP has been frequently applied on various kind of engineering problems and ...

Genetic programming (GP) is recognized as a robust machine learning method for rainfall-runoff modelling. However, it may produce lagged forecasts if autocorrelation feature of runoff series is not taken carefully into ...

Chaos theory is integrated with Multi-Gene Genetic Programming (MGGP) engine as a new hybrid model for river flow forecasting. This is to be referred to as Chaos-MGGP and its performance is tested using daily historic flow ...